Class RegressionProto.RegressionEvaluationMetrics.Builder (2.83.0)

public static final class RegressionProto.RegressionEvaluationMetrics.Builder extends GeneratedMessage.Builder<RegressionProto.RegressionEvaluationMetrics.Builder> implements RegressionProto.RegressionEvaluationMetricsOrBuilder

Metrics for regression problems.

Protobuf type google.cloud.automl.v1beta1.RegressionEvaluationMetrics

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

build()

public RegressionProto.RegressionEvaluationMetrics build()
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics

buildPartial()

public RegressionProto.RegressionEvaluationMetrics buildPartial()
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics

clear()

public RegressionProto.RegressionEvaluationMetrics.Builder clear()
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder
Overrides

clearMeanAbsoluteError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearMeanAbsoluteError()

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearMeanAbsolutePercentageError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearMeanAbsolutePercentageError()

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearRSquared()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRSquared()

Output only. R squared.

float r_squared = 4;

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearRootMeanSquaredError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRootMeanSquaredError()

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearRootMeanSquaredLogError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRootMeanSquaredLogError()

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

getDefaultInstanceForType()

public RegressionProto.RegressionEvaluationMetrics getDefaultInstanceForType()
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
Descriptor
Overrides

getMeanAbsoluteError()

public float getMeanAbsoluteError()

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Returns
Type Description
float

The meanAbsoluteError.

getMeanAbsolutePercentageError()

public float getMeanAbsolutePercentageError()

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Returns
Type Description
float

The meanAbsolutePercentageError.

getRSquared()

public float getRSquared()

Output only. R squared.

float r_squared = 4;

Returns
Type Description
float

The rSquared.

getRootMeanSquaredError()

public float getRootMeanSquaredError()

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Returns
Type Description
float

The rootMeanSquaredError.

getRootMeanSquaredLogError()

public float getRootMeanSquaredLogError()

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Returns
Type Description
float

The rootMeanSquaredLogError.

internalGetFieldAccessorTable()

protected GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeFrom(RegressionProto.RegressionEvaluationMetrics other)

public RegressionProto.RegressionEvaluationMetrics.Builder mergeFrom(RegressionProto.RegressionEvaluationMetrics other)
Parameter
Name Description
other RegressionProto.RegressionEvaluationMetrics
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public RegressionProto.RegressionEvaluationMetrics.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public RegressionProto.RegressionEvaluationMetrics.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder
Overrides

setMeanAbsoluteError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setMeanAbsoluteError(float value)

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Parameter
Name Description
value float

The meanAbsoluteError to set.

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setMeanAbsolutePercentageError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setMeanAbsolutePercentageError(float value)

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Parameter
Name Description
value float

The meanAbsolutePercentageError to set.

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setRSquared(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRSquared(float value)

Output only. R squared.

float r_squared = 4;

Parameter
Name Description
value float

The rSquared to set.

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setRootMeanSquaredError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRootMeanSquaredError(float value)

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Parameter
Name Description
value float

The rootMeanSquaredError to set.

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setRootMeanSquaredLogError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRootMeanSquaredLogError(float value)

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Parameter
Name Description
value float

The rootMeanSquaredLogError to set.

Returns
Type Description
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.